可再生能源项目投资风险“识别-评估-预警”联动模型：基于“一带一路”共建国家案例

doi:10.16381/j.cnki.issn1003-207x.2024.1609

Abstract

Abstract:

Growing global investments in renewable energy have heightened worldwide attention to risks stemming from uncertainties. Under China’s Belt and Road Initiative （BRI）， increased investments in host-country renewable energy projects underscore the critical need for effective risk management. A risk identification-assessment-early warning’ framework is employed to analyze investment risks across 64 BRI countries. Using data volatility （standard deviation） as a core metric， 2021 risks and project trends for 2023-2024 are quantified. First， an integrated risk model is constructed： BERTopic identifies risk themes， an entropy-weighted CRITIC model with Gaussian mixture distribution assesses risks based on standard deviation， and an early-warning system combines GM（1，1） forecasting with firefly algorithm-optimized SVM. Second， seven key risk dimensions are identified： political， economic， socio-environmental， market， technological， energy resource， and operational management. In 2021， risk levels varied substantially： 8 high-risk countries （e.g.， Yemen， Afghanistan）， 10 medium-high-risk （e.g.， Iraq， Turkey）， 11 medium-risk （e.g.， Mongolia， Indonesia）， 13 medium-low-risk （e.g.， Brunei）， and 22 low-risk （e.g.， Singapore）. Projections indicate 48 countries will experience risk-level shifts by 2023–2024， with 11 countries （e.g.， Malaysia， Israel， Ukraine） facing elevated risks. Third， installed capacity and power generation volatility emerge as critical indicators. Installed capacity reflects renewable energy development potential， while generation volatility signals technological maturity—countries with higher maturity exhibit better fluctuation control， ensuring stable supply and risk mitigation. Key policy insights are offered： Chinese investors should adopt granular strategies focused on sector-specific risks rather than relying solely on country risk ratings. Governments should strengthen BRI cooperation， enhance policy frameworks， and optimize financing environments to reduce investment risks. By centering on data volatility， investors with decision-support tools and advances risk assessment precision for China's BRI renewable energy investments are provided.

Key words: renewable energy, investment risk identification, risk assessment, risk alert, The Belt and Road Initiative

CLC Number:

F283

Hao Ding,Yu Su,Dequn Zhou, et al. 'Identification-Assessment-Alert' Integration Model of Investment Risks in Renewable Energy Projects: Cases of Belt and Road Countries[J]. Chinese Journal of Management Science, 2025, 33(11): 345-356.

Figures/Tables 14

References 40

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投资风险等级	国家
高风险（Ⅴ级）	缅甸、菲律宾、伊朗、印度、巴基斯坦、孟加拉国、阿富汗、也门
中高风险（Ⅳ级）	伊拉克、土耳其、叙利亚、黎巴嫩、埃及、乌兹别克斯坦、土库曼斯坦、俄罗斯、白俄罗斯、阿塞拜疆
中风险（Ⅲ级）	蒙古国、印度尼西亚、泰国、老挝、柬埔寨、越南、斯里兰卡、尼泊尔、塔吉克斯坦、吉尔吉斯斯坦、波黑
中低风险（Ⅱ级）	文莱、约旦、科威特、马尔代夫、不丹、亚美尼亚、摩尔多瓦、立陶宛、爱沙尼亚、黑山、罗马尼亚、保加利亚、北马其顿
低风险（Ⅰ级）	新加坡、马来西亚、以色列、沙特阿拉伯、阿曼、阿联酋、卡塔尔、巴林、希腊、塞浦路斯、哈萨克斯坦、乌克兰、格鲁吉亚、波兰、拉脱维亚、捷克、斯洛伐克、匈牙利、斯洛文尼亚、克罗地亚、塞尔维亚、阿尔巴尼亚

模型精度等级	p	C	预测结果占比（%）
一级（好）	0.95≤p	C≤0.35	94.32
二级（合格）	0.85≤p<0.95	0.35<C≤0.50
三级（勉强）	0.70≤p<0.80	0.50<C≤0.65
四级（不合格）	p<0.70	0.65<C	5.68

评估项目	精确度	召回率	F1分数	Support
1(低风险)	0.90	0.82	0.86	11
2(中风险l)	0.60	0.75	0.67	4
3(高风险)	1.00	1.00	1.00	7
合计	0.86	0.85	0.84	22
宏平均	0.83	0.86	0.84	22
权重平均	0.88	0.86	0.87	22
准确率	0.86			22

'Identification-Assessment-Alert' Integration Model of Investment Risks in Renewable Energy Projects: Cases of Belt and Road Countries

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